Search results for "Gauss"

Bayesian semiparametric long memory models for discretized event data

2020

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…

Noise phenomena and soliton dynamics in long Josephson junctions

2013

In this work we computationally explore the transient dynamics of a noisy Josephson junction (JJ). Principal purpose is to investigate the behavior of the lifetime of the superconductive state as a function of the system and noise source parameters. The relations between the emerging phenomena and the evolution of the JJ order parameter φ, that is the phase difference between the macroscopic wave functions describing the superconducting condensate in the two electrodes, is deeply investigated. We focus our interest on the switching events from the superconducting metastable state, and in particular on the mean escape time (MET). In the used model, a long JJ can be represented by a string co…

A novel heuristic algorithm for the modeling and risk assessment of the COVID-19 pandemic phenomenon

2020

This article belongs to the special issue: Soft computing techniques in materials science and engineering Summarization: The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of dai…

Do the Mega and Titan Tests Yield Accurate Results? An Investigation into Two Experimental Intelligence Tests

2020

The Mega and Titan Tests were designed by Ronald K. Hoeflin to make fine distinctions in the intellectual stratosphere. The Mega Test purported to measure above-average adult IQ up to and including scores with a rarity of one in a million of the general population. The Titan Test was billed as being even more difficult than the Mega Test. In this article, these claims are subjected to scrutiny. Both tests are renormed using the normal curve of distribution. It is found that the Mega Test has a higher ceiling and a lower floor than the Titan Test. While the Mega Test may thus seem preferable as a psychometric instrument, it is somewhat marred by a number of easy items in its verbal section. …

Correspondence between generalized binomial field states and coherent atomic states

2008

We show that the N-photon generalized binomial states of electromagnetic field may be put in a bijective mapping with the coherent atomic states of N two-level atoms. We exploit this correspondence to simply obtain both known and new properties of the N-photon generalized binomial states. In particular, an over-complete basis of these binomial states and an orthonormal basis are obtained. Finally, the squeezing properties of generalized binomial state are analyzed.

Jet fragmentation transverse momentum distributions in pp and p-Pb collisions at √s, √sNN = 5.02 TeV

2021

Jet fragmentation transverse momentum (jT) distributions are measured in proton-proton (pp) and proton-lead (p-Pb) collisions at √sNN = 5.02 TeV with the ALICE experiment at the LHC. Jets are reconstructed with the ALICE tracking detectors and electromagnetic calorimeter using the anti-kT algorithm with resolution parameter R = 0.4 in the pseudorapidity range |η| < 0.25. The jT values are calculated for charged particles inside a fixed cone with a radius R = 0.4 around the reconstructed jet axis. The measured jT distributions are compared with a variety of parton-shower models. Herwig and Pythia 8 based models describe the data well for the higher jT region, while they underestimate the low…

Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes

2018

In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophysical parameter variables under a gap filling setup. In particular, we focus on LAI and fAPAR over rice areas. We show how this problem cannot be solved with standard single-output (SO) GP models, and how the proposed MO-GP models are able to successfully predict these variables even in high missing data regimes, by implicitly performing an across-domain information transfer. CICYT TIN2015-64210-R In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophy…

Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data.

2022

The unprecedented availability of optical satellite data in cloud-based computing platforms, such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval models from the local to the planetary scale. Hybrid retrieval models are of interest to run in these platforms as they combine the advantages of physically-based radiative transfer models (RTM) with the flexibility of machine learning regression algorithms. Previous research with GEE primarily relied on processing bottom-of-atmosphere (BOA) reflectance data, which requires atmospheric correction. In the present study, we implemented hybrid models directly into GEE for processing Sentinel-2 (S2) Level-1C (L1C)…

Corrigendum: ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

2018

Effect of Cycloplegia on Blur Perception Thresholds as Measured by Source Method

2017

Abstract One of the advantages of a source method over observer method in blur perception measurements is better control of a stimulus blur level, which is achieved with computerised image processing unlike the observer method that requires optical defocusing of the observer. The aim of this study was to determine if paralysation of accommodation has effect on blur perception thresholds, thereby evaluating its necessity in such experiments. Blur perception thresholds (just noticeable blur, clear image, recognition, and non-resolvable blur thresholds) were evaluated with (using cycloplegia) and without paralysed accommodation to determine effect on blur perception. A computerised low-pass sp…